A Comparison of WebRTC and Conventional Videoconferencing for Synchronized Remote Medical Image Presentation.
J Digit Imaging
; 35(1): 68-76, 2022 02.
Artículo
en Inglés
| MEDLINE | ID: covidwho-1588786
ABSTRACT
DICOM viewers must fulfill roles beyond primary diagnostic interpretation, including serving as presentation tools in teaching and multidisciplinary conferences, thereby enabling multiple individuals to review images collaboratively in real time. When in-person gathering is not possible, a variety of solutions have been deployed to maintain the ability for spatially separated users to view medical images simultaneously. These approaches differ in their backend architectures, utilization of application-specific optimizations, and ultimately in their end user satisfaction. In this work, we systematically compare the performance of conventional screensharing using a videoconferencing application with that of a custom, synchronized DICOM viewer linked using Web Real Time Communications (WebRTC) technology. We find superior performance for the WebRTC method with regard to image quality and latency across a range of simulated adverse network conditions, and we show how increasing the number of conference participants differentially affects the bandwidth requirements of the two viewing solutions. In addition, we compare these two approaches in a real-world teaching scenario and gather the feedback of trainee and faculty radiologists, who we found to favor the WebRTC method for its decreased latency, improved image quality, ease of setup, and overall experience. Ultimately, our results demonstrate the value of application-specific solutions for the remote synchronized viewing of medical imaging, which, given the recent increase in reliance on remote collaboration, may constitute a significant consideration for future enterprise viewer procurement decisions.
Texto completo:
Disponible
Colección:
Bases de datos internacionales
Base de datos:
MEDLINE
Asunto principal:
Comunicación
/
Comunicación por Videoconferencia
Límite:
Humanos
Idioma:
Inglés
Revista:
J Digit Imaging
Asunto de la revista:
Diagnóstico por Imagen
/
Informática Médica
/
Radiología
Año:
2022
Tipo del documento:
Artículo
País de afiliación:
S10278-021-00544-0
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